Fluctuation correlations as major determinants of structure- and dynamics-driven allosteric effects

Area of Science:

• Biophysics
• Computational Biology
• Structural Biology

Background:

• Allosteric control regulates biological functions via stimuli at distant protein sites.
• Correlations between protein sites aid in identifying allosteric sites and drug design.
• The precise link between correlation types and allostery remains unclear.

Purpose of the Study:

• To investigate the relationship between various correlation types and allosteric effects.
• To differentiate between structure-driven and dynamics-driven allostery.
• To quantify the distance dependence of allosteric capacity.

Main Methods:

• Utilized perturbation-theory analysis and numerical calculations.
• Employed an anisotropic network model (ANM) to study protein dynamics.
• Analyzed both structure- and dynamics-driven allosteric effects.

Main Results:

• Allostery is determined by covariance of distance fluctuations, not displacement or time-delayed correlations.
• Dynamics-driven allostery is 1-2 orders of magnitude weaker than structure-driven allostery.
• Allosteric capacity decays exponentially with distance (7-10 Å for structure, 4-5 Å for dynamics).

Conclusions:

• Distance fluctuation covariance is key to allosteric regulation.
• Structure-driven allostery is more potent and has a longer range than dynamics-driven allostery.
• The anisotropic network model's cutoff distance influences allosteric effect analysis.